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Towards persuasive social recommendation: knowledge model

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Towards persuasive social recommendation: knowledge model

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dc.contributor.author Palanca Cámara, Javier es_ES
dc.contributor.author Heras Barberá, Stella María es_ES
dc.contributor.author Jorge Cano, Javier es_ES
dc.contributor.author Julian Inglada, Vicente Javier
dc.date.accessioned 2016-04-08T08:59:44Z
dc.date.available 2016-04-08T08:59:44Z
dc.date.issued 2015-06
dc.identifier.issn 1559-6915
dc.identifier.uri http://hdl.handle.net/10251/62358
dc.description.abstract [EN] The exponential growth of social networks makes fingerprint let by users on the Internet a great source of information, with data about their preferences, needs, goals, profile and social environment. These data are distributed across di↵erent sources of information (social networks, blogs, databases, etc.) that may contain inconsistencies and their accuracy is uncertain. Paradoxically, this unprecedented availability of heterogeneous data has meant that users have more information available than they actually are able to process and understand to extract useful knowledge from it. Therefore, new tools that help users in their decision-making processes within the network (e.g. which friends to contact with or which products to consume) are needed. In this paper, we show how we have used a graph-based model to extract and model data and transform it in valuable knowledge to develop a persuasive social recommendation system1. es_ES
dc.description.sponsorship This work was partially supported by the project MINE-CO/FEDER TIN2012-365686-C03-01 of the Spanish government and by the Spanish Ministry of Education, Culture and Sports under the Program for R&D Valorisation and Joint Resources VLC/CAMPUS, as part of the Campus of International Excellence Program (Ref. SP20140788).
dc.language Inglés es_ES
dc.relation.ispartof ACM SIGAPP Applied Computing Review es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Recommender systems es_ES
dc.subject Data integration es_ES
dc.subject Social networks es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Towards persuasive social recommendation: knowledge model es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1145/2815169.2815173
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2012-36586-C03-01/ES/SOCIEDADES HUMANO-AGENTE: DISEÑO, FORMACION Y COORDINACION/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MECD//SP20140788/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Palanca Cámara, J.; Heras Barberá, SM.; Jorge Cano, J.; Julian Inglada, VJ. (2015). Towards persuasive social recommendation: knowledge model. ACM SIGAPP Applied Computing Review. 15(2):41-49. https://doi.org/10.1145/2815169.2815173 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1145/2695664.2695732 es_ES
dc.description.upvformatpinicio 41 es_ES
dc.description.upvformatpfin 49 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 15 es_ES
dc.description.issue 2 es_ES
dc.relation.senia 292921 es_ES
dc.contributor.funder Ministerio de Economía y Competitividad
dc.contributor.funder Ministerio de Educación, Cultura y Deporte
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